Despite the fact that contraceptives have the potential to nearly eliminate pregnancy and sexually transmitted diseases (STDs), data from the 2002 National Survey of Family Growth show that almost half the pregnancies are unintended (and approximately half of them end in an abortion) and STDs continue to be a major health threat (19 million STD infections occur annually, Centers for Disease Control and Prevention, 2003). Perhaps, if we better understood contraceptive choices, we could recommend more appropriate methods to individual women, develop better health interventions and social marketing campaigns, and conceive more satisfactory contraceptives;and thereby lower unintended pregnancies and STDs. This project combines recent advances in data collection and modeling of discrete choices by the principal investigator (PI) to advance our understanding of contraceptive choices. Specifically, while previous studies of contraceptive choice have usually sought to model the reduced-form relationship between socioeconomic characteristics and method choice, we take a more structural econometric approach. We model variation in contraceptives chosen as arising from differences in the importance of attributes of contraceptives (e.g., preventing conception, preventing transmission of STDs, side-effects, and cost) and differences in the perceived characteristics of those contraceptives. Our data-a supplement to the NLS-Y97 designed by the PI-directly measure individual perceptions (or expectations) of the attributes of contraceptives and the perceived characteristics of the contraceptives. Our econometric model is designed to analyze data of this form. The resulting parameter estimates allow us to simulate the effect of policies (e.g., price subsidies or information campaigns) on contraceptive choice and unintended pregnancy. The specific aims of the research are to: (1) understand how women's subjective expectations about birth control methods'attributes vary according to socioeconomic characteristics;(2) assess the accuracy of women's perceptions of the efficacy of birth control methods by comparing perceptions with the best clinical evidence, (3) estimate women's preferences about birth control methods'attributes using a structural utility framework, (4) evaluate how preferences vary by observable characteristics and quantify the relative weight of various attributes in a women's decision to use a method;and (5) simulate the effect of policies on contraception use and unintended pregnancies.